The targeted removal of efficient but toxic corrosion inhibitors based on hexavalent chromium has provided an impetus for discovery of new, more benign organic compounds to fill that role. Developments in high-throughput synthesis of organic compounds, the establishment of large libraries of available chemicals, accelerated corrosion inhibition testing technologies, the increased capabilities of machine learning (ML) methods, and a better understanding of mechanisms of inhibition provide the potential to make discovery of new corrosion inhibitors faster and cheaper than ever before. These technical developments in the corrosion inhibition field are summarized herein. We describe how data-driven machine learning methods can generate models linking molecular properties to corrosion inhibition that can be used to predict the performance of materials not yet synthesized or tested. The literature on inhibition mechanisms is briefly summarized along with quantitative structure–property relationships models of small organic molecule corrosion inhibitors. The success of these methods provides a paradigm for the rapid discovery of novel, effective corrosion inhibitors for a range of metals and alloys, in diverse environments. A comprehensive list of corrosion inhibitors tested for various substrates that was curated as part of this review is accessible online https://excorr.web.app/database and available in a machine-readable format.

A 2D finite element model is developed to simulate the protection of active protective coatings in a defect. The leaching kinetics, inhibitor-electrolyte reactions and electrochemical surface reactions on homogenized AA2024-T3, are considered. Changes in local oxygen distribution, pH, and current density over time are validated using surface scanning micro-probe techniques. The limitations posed by the prediction of surface current density at the metal interface using a FEM model with a homogenized microstructure are identified and addressed. The validated FEM is then used to predict inhibitor concentration and pH dependent on the initial inhibitor pigment concentration in an organic coating.

Creating durable, eco-friendly coatings for long-term corrosion protection requires innovative strategies to streamline design and development processes, conserve resources, and decrease maintenance costs. In this pursuit, machine learning emerges as a promising catalyst, despite the challenges presented by the scarcity of high-quality datasets in the field of corrosion inhibition research. To address this obstacle, we have created an extensive electrochemical library of around 80 inhibitor candidates. The electrochemical behaviour of inhibitor-exposed AA2024-T3 substrates was captured using linear polarisation resistance, electrochemical impedance spectroscopy, and potentiodynamic polarisation techniques at different exposure times to obtain the most comprehensive electrochemical picture of the corrosion inhibition over a 24-h period. The experimental results yield target parameters and additional input features that can be combined with computational descriptors to develop quantitative structure–property relationship (QSPR) models augmented by mechanistic input features.

Integrated attenuated total reflection – Fourier transform infrared spectroscopy (ATR-FTIR) – Electrochemical impedance spectroscopy (EIS) measurements were used to simultaneously follow chemisorption mechanisms of organic inhibitors as well as their corrosion inhibition efficiency towards magnesium based substrates. Four carboxylic compounds, i.e. 2,5-pyridinedicarboxylic acid (PDC), 3-methylsalicylic acid (MSA), sodium salicylate (SS) and fumaric acid (FA), were selected based on their promising inhibiting capacities and were all shown to chemisorb at the MgO/Mg(OH)₂ surface by carboxylate bond formation. Orientation analysis using polarized infrared light showed that carboxylate bonds established using aliphatic carboxylate compound aligned perpendicular to the magnesium surface, whereas carboxylate bonds with aromatic compounds were oriented in plane with the magnesium surface. This different orientation is associated to the involvement of π-interactions in the MgO/Mg(OH)₂ – aromatic carboxylate adsorption. Additionally, DFT calculations revealed that the addition of hetero-atoms (i.e. N or OH) in the molecular structure contributes to increased adsorption energies, indicating that next to carboxylate groups also these hetero-atoms are involved in interfacial interactions. Integrating the ATR-FTIR setup with an electrochemical cell allowing for simultaneous EIS measurements lead to two surface phenomena determining the inhibition efficiency. Surface hydroxylation processes on one hand forming a MgO/Mg(OH)₂ layer on one hand, and the chemisorption of carboxylate compounds on the other hand. The inhibition efficiency was found to increase in following order: FA < PDC < MSA and was mainly associated to the formation of a MgO/Mg(OH)₂ layer. SS was shown to act as a corrosion accelerator rather than a corrosion inhibitor. Despite its high sensitivity for water, both surface processes could be followed in situ by means of ATR-FTIR. Simultaneously, protective properties of the formed films could be quantified by means of EIS. Consequently, integrated ATR-FTIR – EIS methodology has shown to be highly valuable for gaining in-situ insights in the inhibition mechanism, while quantifying the inhibition efficiency. This was even possible for highly active metal substrate as magnesium, although further developments are suggested if one aims to quantify electrochemical constants related to corrosion and other surface processes measured at the low frequencies (i.e. < 1 Hz).

One of the main applications of SVET in corrosion research is the study of the corrosion inhibition effectiveness and the evaluation of the self-healing effect of inhibitor-containing coatings. The tip of the platinum/iridium vibrating electrode is electroplated with black platinum, which creates a large electrode surface and confers high capacitance to the tip. When studying organic inhibitors in aqueous solutions with SVET, inhibitor adsorption may occur at the tip, causing its contamination and the initial calibration conditions of the system might not be valid. This may lead to an incorrect interpretation of the results. This work is intended to study the effect of different inhibitors (cerium nitrate, 8-hydroxyquinoline, potassium 2,5-dimercapto-1,3,4-thiadiazolate, benzotriazole and mercaptobenzothiazole), typically used for corrosion protection of aluminum alloys, on the Pt probe signal during SVET measurements. The results reveal the detrimental effect of some corrosion inhibitors on the sensitivity of the vibrating probe, an effect that imposes a regular assessment of the electrode state during measurements. The increase of the signal noise was related to a decrease of the probe capacitance, while the false current density signal was a result of the potential drift between vibrating and reference electrodes.